Python prepare_for_training Exemples

Exemple #1

Fichier : 09-02-2020.py Projet : mikkoim/benthic

from sklearn.utils import shuffle

df_train = shuffle(df_train)
df_val = shuffle(df_val)

#%% Create TF dataloader
AUTOTUNE = tf.data.experimental.AUTOTUNE
IMSIZE = (224, 224, 3)
BATCH_SIZE = 8

train_ds = create_tf_dataset(df_train, imsize=IMSIZE, onehot=True)

val_ds = create_tf_dataset(df_val, imsize=IMSIZE, onehot=True)

train_ds = prepare_for_training(train_ds,
                                shuffle_buffer_size=1000,
                                batch_size=BATCH_SIZE)

val_ds = prepare_for_training(val_ds,
                              shuffle_buffer_size=1000,
                              batch_size=BATCH_SIZE)

for image, label in train_ds.take(5):
    print(image.shape)
    print(label.shape)

#%% Custom loss

import tensorflow.keras.backend as K

Exemple #2

Fichier : 12-01-2020_2.py Projet : mikkoim/benthic

df_val = create_df(os.path.join(datapath, val_fname),
                     img_path,
                     partial_dataset=part_dat,
                     seed=123)

#%% Create TF dataloader
AUTOTUNE = tf.data.experimental.AUTOTUNE
IMSIZE = (224,224,3)
BATCH_SIZE = 8

train_ds = create_tf_dataset(df_train, imsize=IMSIZE, onehot=True)
val_ds = create_tf_dataset(df_val, imsize=IMSIZE, onehot=True)


train_ds = prepare_for_training(train_ds, 
                                shuffle_buffer_size=len(df_train),
                                batch_size=BATCH_SIZE)

val_ds = prepare_for_training(val_ds, 
                              shuffle_buffer_size=len(df_val),
                              batch_size=BATCH_SIZE)

for image, label in train_ds.take(5):
    print(image.shape)
    print(label.shape)


#%% NN Model

from tensorflow.keras.models import Model
from tensorflow.keras.applications.inception_v3 import InceptionV3